AWS Machine Learning Blog

OCTOBER 24, 2024

Conventional ML development cycles take weeks to many months and requires sparse data science understanding and ML development skills. Business analysts’ ideas to use ML models often sit in prolonged backlogs because of data engineering and data science team’s bandwidth and data preparation activities.

Data Warehouse 113

Data Warehouse Machine Learning Machine Learning Cloud Data 113

Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. Here we use RedshiftDatasetDefinition to retrieve the dataset from the Redshift cluster. We attached the IAM role to the Redshift cluster that we created earlier.

ML 123

ML ML AWS Data Warehouse 123

phData

DECEMBER 4, 2023

However, if there’s one thing we’ve learned from years of successful cloud data implementations here at phData, it’s the importance of: Defining and implementing processes Building automation, and Performing configuration …even before you create the first user account. In this case, the max cluster count should also be two.

Clustering 98

Clustering Database SQL Data Pipeline 98

AWS Machine Learning Blog

NOVEMBER 16, 2023

These environments ranged from individual laptops and desktops to diverse on-premises computational clusters and cloud-based infrastructure. Access to AWS environments SageMaker and associated AI/ML services are accessed with security guardrails for data preparation, model development, training, annotation, and deployment.

ML 121

ML ML AWS AI 121

phData

FEBRUARY 7, 2024

The Snowflake Data Cloud is a leading cloud data platform that provides various features and services for data storage, processing, and analysis. A new feature that Snowflake offers is called Snowpark, which provides an intuitive library for querying and processing data at scale in Snowflake.

Python 52

Python ML ML SQL 52

Snorkel AI

MAY 26, 2023

And that’s really key for taking data science experiments into production. And we view Snowflake as a solid data foundation to enable mature data science machine learning practices. And how we do that is by letting our customers develop a single source of truth for their data in Snowflake. PA : Got it.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

And that’s really key for taking data science experiments into production. And we view Snowflake as a solid data foundation to enable mature data science machine learning practices. And how we do that is by letting our customers develop a single source of truth for their data in Snowflake. PA : Got it.

SQL 52

SQL ML ML Python 52